Labor Force Statistics Dataset
Introduction
In the midst of political, social, and economic polarization induced by COVID outbreaks, it would be interesting to explore the new dynamics of the labor force. Particularly, we will focus on the intersecting components of employment and recession: gender, race, age, income level, etc. By doing so, we hope to discover and understand the stories behind the numbers.
This is our report of the Labor Force Statistics Dataset from the U.S. Bureau of Labor Statistics, Current Population Survey’s Labor Force Statistics. The Current Population Survey (CPS) is a monthly survey of households conducted by the Bureau of Census for the Bureau of Labor Statistics. It provides a comprehensive body of data on the labor force, employment, unemployment, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics.
Summary Information
Some quick information that we extracted from our summary information functions was that women had a higher max unemployment rate of 15.5% versus males with 13%. We also found that among people with different education levels, those those with less education (less than high school diploma or only highschool diploma) had higher max unemployment rates, 17.3% to 21.2% than those with higher education (some college or bachelors and higher), 8.4% to 15%. Finally among different races, hispanic/latino Americans had the highest max unemployment rate of 18.9% while white Americans had the lowest unemployment rate of just 14.2%. Interestingly all these max unemployment rates were in 2020, showing the devastating impact COVID has had on all Americans.
Table Findings
Below is a unemployment table with features that reflect questions that we are trying to answer. Specifically, since we are primarily interested in the on the impact COVID had on American with different demographics, there are columns of sex, race and education. The table shows the max unemployment rate of each year. We sorted the data in descending year order so it is easy to compare 2020 with previous years. As you can see, the unemployment rates of 2020 is significantly higher than the previous years. Even compared to the regression in 2008, 2020 unemployment is significantly higher
Year <int> | Men <dbl> | Women <dbl> | Bachelor_Degree_or_Higher <dbl> | High_School_Grad <dbl> | Some_High_School <dbl> | |
|---|---|---|---|---|---|---|
| 2020 | 13.0 | 15.5 | 8.4 | 17.3 | 21.2 | |
| 2019 | 3.7 | 3.6 | 2.4 | 3.9 | 5.8 | |
| 2018 | 3.8 | 3.8 | 2.3 | 4.4 | 5.9 | |
| 2017 | 4.3 | 4.4 | 2.5 | 5.2 | 7.7 | |
| 2011 | 9.0 | 8.2 | 4.5 | 10.0 | 14.7 | |
| 2010 | 10.3 | 8.4 | 5.0 | 11.0 | 15.8 | |
| 2009 | 10.4 | 8.0 | 5.0 | 11.0 | 15.6 | |
| 2008 | 7.4 | 5.9 | 3.6 | 7.8 | 11.1 |
Education Graph
Below is a chart intended to show the relationship between Education and Unemployment Rate:
During times like these, with vast unemployment rates, many students like us are struggling with school. But does education level really impact one’s chances of being unemployed? This graph seeks to answer that problem. As we can see, there was a significant spike in unemployment in 2020 based on education levels. Notably, those with lower education levels, some high school or just high school, were hit the worst by COVID-19 as their unemployment rates skyrocketed. On the other hand, those with higher education, were not as significantly impacted.
Gender Graph
Below is a chart intended to show the relationship between Gender and Unemployment Rate in 2020:
The gender gap between sexes has always been a issue throughout history. Specifically as the result of COVID, how large, if any, is the gender gap between men and women. Surprisingly, our graph reveals that the unemployment rate between men and women as mostly been the same this past year. For 5 of the past months, the unemployment rate has been less than a 1% difference. However, notably for April 2019, when COVID began taking a significant toll on Americans, the unemployment difference was the largest its been this past year with about a 3% difference.
